Rendley MCP
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Rendley MCPcreate a 30-second promo video for my new product"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Rendley MCP
The MCP server for Rendley. It gives an AI assistant a full video editor: connect it once, then create and edit video by describing what you want, in the same chat you already work in. Under the hood it drives the hosted Rendley editor in a browser and calls the hosted Rendley API on your behalf:
Editor:
https://app.rendley.comAPI:
https://api.rendley.com/v1
The same agent is also reachable over plain HTTP (POST /v1/agent) for backends that don't speak MCP. See REST example.
There are two ways to use it:
Use the hosted server at
https://mcp.rendley.com/mcp. Nothing to run. See Connect a client.Self-host this server against the hosted Rendley API. See Self-host the server.
📖 Full documentation, with step-by-step setup guides and screenshots: docs.rendley.com/mcp
Connect a client
Any client that speaks remote MCP can connect. Point it at the endpoint and authenticate by signing in or with an API key:
https://mcp.rendley.com/mcpSign in with Rendley (recommended): the client opens a Rendley sign-in tab and you approve access. Nothing to copy, and you can revoke it later.
API key: the client sends an
Authorization: Bearer YOUR_RENDLEY_API_KEYheader. Create one at Settings → API Keys; see Get an API key.
Most clients accept a JSON config like this:
{
"mcpServers": {
"rendley": {
"url": "https://mcp.rendley.com/mcp",
"headers": { "Authorization": "Bearer YOUR_RENDLEY_API_KEY" }
}
}
}For sign-in, drop the headers block and let the client run the browser flow.
The docs have illustrated, per-client walkthroughs:
Claude: desktop, web, and Claude Code.
Codex: the Codex desktop app and CLI.
Other clients: any other client that speaks remote MCP, plus the
mcp-remotebridge for local-only clients.
For Claude Code specifically:
claude mcp add --transport http rendley https://mcp.rendley.com/mcp \
--header "Authorization: Bearer YOUR_RENDLEY_API_KEY"Try it
Ask the client what it can do, then try a simple request:
What can Rendley do here?
List my projects.
If it lists the Rendley tools and your projects, you're connected. From there, describe the video you want and the assistant creates a project, builds the edit, and returns a link.
Related MCP server: CapCut MCP Server
Self-host the server
This repo is the MCP server only; it does not run the full Rendley stack locally. It talks to the hosted Rendley API and editor. When you self-host, point clients at your own https://<host>/mcp instead of https://mcp.rendley.com/mcp.
Requirements
Bun
>= 1.1(or Docker)A Rendley account to connect with. Clients authenticate per request with their own API key (Settings → API Keys, guide) or OAuth sign-in. The server stores no key of its own.
Run locally
git clone https://github.com/rendleyhq/rendley-mcp.git
cd rendley-mcp
bun install
bun dev # http://localhost:8787API_BASE_URL and APP_BASE_URL default to the hosted Rendley API and editor, so the server boots out of the box with no .env at all; copy .env.example only to point at a different stack. The server holds no credentials of its own: every request authenticates with the caller's own API key or OAuth token.
By default the server drives the editor with a local Chrome (BROWSER_MODE=local), so no extra infrastructure is needed. bun install downloads a bundled Chromium; with USE_CHROME_CHANNEL=true it prefers your installed Google Chrome and falls back to the bundled browser. Set HEADLESS=false to watch the editor in a visible window, and CPU_ONLY=true on machines without a usable GPU.
Verify it's up:
curl http://localhost:8787/health
# {"status":"ok","browser_mode":"local"}Docker
docker compose up -d --build
curl http://localhost:8787/healthConnecting a client to your instance
Use the same client steps as the hosted server, but swap the endpoint for your host (e.g. http://localhost:8787/mcp) and authenticate with your API key as a bearer token:
{
"mcpServers": {
"rendley": {
"url": "http://localhost:8787/mcp",
"headers": { "Authorization": "Bearer YOUR_RENDLEY_API_KEY" }
}
}
}OAuth. OAuth sign-in is always on. Clients that support it (Claude connectors, ChatGPT, codex mcp login rendley) can sign in via the hosted login flow instead of pasting a key; the server advertises the authorization server through RFC 9728 protected-resource metadata. Set MCP_PUBLIC_URL to this server's public URL so discovery points at the right host.
Remote browser mode
For hosted deployments, set BROWSER_MODE=remote and point the server at a deployed remote browser worker. The server mints a short-lived editor session token and posts it to the worker, so the caller's credential never leaves this process:
BROWSER_MODE=remote
BROWSER_WORKER_URL=https://<your-browser-worker-host>
BROWSER_WORKER_TOKEN=<must match the worker's secret>Configuration
All configuration is via environment variables; start from .env.example, which documents every option. The essentials:
Variable | Default | Purpose |
|
| Rendley API root. Override for staging or a self-hosted stack. |
|
| Rendley editor root. Override for staging or a self-hosted stack. |
| none | This server's public URL, advertised for OAuth discovery. |
|
|
|
|
| Local mode only; |
|
| Local mode only; prefer installed Chrome over bundled Chromium. |
|
| Force software WebGL (SwiftShader) on hosts without a GPU. |
|
| Max concurrent browser-backed jobs per container. |
| none | CSV allowlist of browser origins. Empty disables CORS. |
Endpoints
Method | Path | |
|
| MCP Streamable HTTP transport |
|
| Start an async edit job |
|
| Poll a job |
|
| Liveness |
REST example
You don't need an MCP client to drive the agent. The same agent is available over plain HTTP. Start a job, get an id back, and poll until the video is ready. Full reference: docs.rendley.com/mcp/api-access.
# Start a job (swap in http://localhost:8787 for a self-hosted instance)
curl -X POST https://mcp.rendley.com/v1/agent \
-H "Authorization: Bearer $RENDLEY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "Create a 9:16 slideshow from these files",
"files": [
{ "url": "https://cdn.example.com/photo1.jpg" },
{ "url": "https://cdn.example.com/photo2.jpg" }
]
}'
# Poll it
curl -H "Authorization: Bearer $RENDLEY_API_KEY" \
https://mcp.rendley.com/v1/jobs/<job_id>Runtime notes
Single tenant per instance.
The browser launches lazily on the first browser-backed request; concurrent requests reuse it via separate tabs, which close on completion.
Media attachments are public URLs only. The editor imports them via the batch upload API (no local-file uploads through MCP).
REST jobs are asynchronous and must be polled. Job state is held in memory: completed records are retained for 1 hour, and a restart drops all job state (in-flight jobs are lost, finished results become unfetchable).
/healthis healthy whenever the server can serve; browser launch failures surface on browser-backed requests.
Scripts
bun dev # watch mode, pretty logs
bun start # production start
bun run typecheckLicense
Apache License 2.0. © 2026 Rendley.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- FlicenseAqualityFmaintenanceEnables AI assistants to create and edit professional videos through natural language by automating JianYing (CapCut) video production workflows. Supports adding media segments, effects, transitions, animations, and exporting editable project files.Last updated20270
- AlicenseAqualityBmaintenanceEnables AI assistants to fully control CapCut video editing projects, including creating projects, importing media, adding text/subtitles, managing audio, and editing timelines.Last updated251MIT
- Alicense-qualityDmaintenanceEnables AI agents to edit videos through natural language, providing tools for timeline editing, audio management, rendering, and more.Last updated2MIT
- Alicense-qualityDmaintenanceEnables AI assistants to generate, manage, and download AI-generated videos using OpenAI's Sora models, supporting text prompts, image-to-video, remixing, and more.Last updatedMIT
Related MCP Connectors
Make videos and docs with your AI agent — describe what you need, every output stays editable.
A real timeline video editor for AI agents: journaled edits, FFmpeg/MLT rendering, exports
Produce complete AI videos from a brief with Maestro
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/rendleyhq/mcp.rendley.com'
If you have feedback or need assistance with the MCP directory API, please join our Discord server